Terra

Terra — named for the earth goddess who knows every fault line in the ground — is an autonomous AI pentester with persistent memory. Where security tools only flag issues, Terra acts like an attacker: it chains exploits across laptops, source control, cloud IAM, and databases, re-proves each of the dozens of vulnerabilities it surfaces with real evidence (validated, not detected), and pairs every finding with a concrete patch or PR. Its edge is memory — every exploit attempt, target fingerprint, and outcome lives in MongoDB Atlas, and before each move Terra vector-searches its past engagements to re-order its attack plan, so what it learned at one organization sharpens what it does at the next. The result is mechanical: our model stalls cold and scores 30/100, but with a single memory retrieved from a different engagement it crosses the wall and finishes at 100/100 — same model, same target, the only variable is MongoDB. Built on Atlas Vector Search for memory and LangGraph for crash-safe, resumable runs.